关键词：
Design for manufacturing;Topology optimization;Stress constraints;Connectivity constraint;Aggregation technique
摘要：
Structural topology optimization considering both performance and manufacturability is very attractive in engineering applications. This work proposes a formulation for structural topology optimization to achieve such a design, in which material strength, structural stiffness, and connectivity are simultaneously considered by integrating stress and simply-connected constraints into the compliance minimization problem. An effective solution algorithm consisting of different optimization techniques is introduced to handle various numerical difficulties resulted from this relatively complex multi-constraint and multi-field problem. Except for the stress penalization and aggregation techniques, the regional measure strategy is used together with the stability transformation method-based correction scheme to address stress constraints, which is also applied to the Poisson equation-based scalar field constraint in the simply-connected constraint. Numerical examples are presented to assess the features of the achieved design along with the performance of the employed algorithm. Comparisons with pure compliance, pure stress, and pure connectivity designs are provided to illustrate differences arising in the proposed design with respect to traditional approaches, also the necessity. Innovative manufacturing-oriented designs with consideration of the strength, stiffness, and connectivity are now available.
关键词：
Design for manufacturing;Topology optimization;Enclosed voids;Additive manufacturing;Traditional manufacturing
摘要：
Suppressing enclosed voids in topology optimization is an important problem in design for manufacturing. The method of Poisson equation-based scalar field constraint (i.e., Poisson method) can effectively address this problem. Nevertheless, the numerical performance of this method is not well understood. This paper investigates the numerical functionality and characteristics of the Poisson method. An electrostatic model is developed to describe this method instead of the previous temperature model. Moreover, an efficient constraint scheme is proposed, which combines density filtering, Heaviside projection, regional measure, and normalization techniques to overcome various numerical issues and difficulties associated with the method. Particularly, the key constraint relation between the constraint threshold and the optimized result in this method is clarified. Numerical examples are presented to assess the Poisson method and demonstrate the effectiveness of the proposed constraint scheme. It is shown that the choice of constraint boundary conditions affects the obtained design. And the constraint effect of the Poisson method depends on the constraint threshold. Besides, the approximation error variations have a significant impact on the constraint relation for the aggregation techniques-based constraint implementation. These findings are essential in obtaining reasonable designs by the Poisson method. (C) 2020 Elsevier Ltd. All rights reserved.
摘要：
This paper proposes a methodology for the topology optimization of continuum structures subject to dynamic stress response constraints under stochastic loads. The topology optimization model is built, where the objective function is the structural weight, and the dynamic stress constraints are applied. In order to greatly reduce the computational cost of dynamic stress responses and prevent stress concentration phenomenon, the P-norm aggregation function is adopted to replace the dynamic stress response constraints. To solve the defined topology optimization problem, a method with varying dynamic stress response limit is presented, and the sensitivities of the equivalent dynamic stress response constraints with respect to the reciprocal design variables is derived so as to form the explicit approximate functions for structural equivalent dynamic stress response constraints. Then, based on dual theory, an algorithm by using nonlinear programming method with simple trust regions is introduced to solve the optimization problem. Finally, the results of several numerical examples are given to demonstrate the validity and effectiveness of the proposed approach.
关键词：
Reliability-based design optimization;Kriging model;Mixed uncertainty model;Probability;Convex set model
摘要：
In many practical applications, probabilistic and bounded uncertainties often arise simultaneously, and these uncertainties can be described by using probability and convex set models. However, the computing cost becomes unacceptable when directly solving the reliability-based design optimization (RBDO) problem with these uncertainties involved. To address this issue, in this study, a sequential sampling strategy by extending classical sequential optimization and reliability assessment (SORA) method for RBDO is developed. The proposed strategy can successively select sample points to update the surrogate model at each step of the optimization process. New samples for reliability constraints are mainly chosen from the local region around the approximate minimum performance target point (MPTP) and worst-case point (WCP). Typical design examples, including one engineering application, are investigated to demonstrate the efficiency and accuracy of the proposed method.
作者机构：
[俞燎宏; 荣见华; 唐承铁; 李方义] School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha;410114, China;School of Physical Science and Technology, Yichun University, Yichun;336000, China;Hunan Province Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle, Changsha University of Science and Technology, Changsha
通讯机构：
[Rong, J.] S;School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
作者机构：
[赵志军; 荣见华; 李方义; 俞燎宏; 陈一雄] School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China;[赵志军; 荣见华; 李方义; 俞燎宏; 陈一雄] Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle, College of Hunan Province, Changsha, 410114, China;[俞燎宏] School of Physical Science and Technology, Yichun University, Yichun, 336000, China
通讯机构：
School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
作者机构：
[石军; 俞燎宏; 唐承铁; 荣见华; 赵志军] School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410076, China;[赵志军] Department of Civil Engineering, Changsha University, Changsha, 410003, China;[唐承铁] Key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle, Changsha University of Science and Technology, Changsha, 410114, China;[荣见华; 俞燎宏] Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle of Hunan Province, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
作者机构：
[赵志军; 黄方林] School of Civil Engineering, Central South University, Changsha, 410075, China;[岳海玲; 赵志军] Key Laboratory for Safety Control of Bridge Engineering, Changsha University of Science &, Technology, Changsha, 410076, China;[赵志军] Department of Civil Engineering, Changsha University, Changsha, 410022, China;[荣见华] School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410076, China
通讯机构：
School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, China
摘要：
The gray problem of displacement constrained topology volume minimization under multiple load cases still is an opening topic of research. A series of topologies with clear profiles generated from an optimization process are very beneficial to method engineering applications. In this paper, a novel displacement constrained optimization approach for black and white structural topology designs under multiple load cases, is proposed to obtain a series of topologies with clear profiles. Firstly, a distribution feature of constraint displacement derivatives is investigated. Secondly, an adaptive adjusting approach of design variable bounds is proposed, and an improved approximate model with varied constraint limits and a volume penalty objective function are constructed. Thirdly, an improved density-based optimization method is proposed for the displacement constrained topology volume minimization under multiple load cases. Finally, several examples are given to demonstrate that the results obtained by the proposed method provide a series of topologies with clear profiles during an optimization process. It is concluded from examples that the proposed method is effective and robust for generating an optimal topology.
